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goodgo-platform/apps/api/src/modules/analytics/infrastructure/services/ai-service.client.ts
Ho Ngoc Hai 79e173938b
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feat(avm): end-to-end AVM v2 schema + POST /analytics/valuation endpoint
Closes the last gap from the tec-2725 branch: the valuation form's v2
extended-features section and POST endpoint can now submit real
predictions through to the Python ensemble model.

Backend
- New DTO apps/api/src/modules/analytics/presentation/dto/predict-valuation.dto.ts
  with all v1 fields + 8 v2 fields (useV2 toggle, distanceToHospital/Park/
  Mall in km, floodZoneRisk enum NONE|LOW|MEDIUM|HIGH, hasElevator/
  Parking/Pool booleans).
- New CQRS handler apps/api/src/modules/analytics/application/queries/
  predict-valuation/ that routes to AVM_SERVICE.estimateValue() with the
  full request body.
- Extend AVMParams (domain) with the same v2 fields + inline v1 fields
  (district, city, bedrooms, bathrooms, floors, frontage, roadWidth,
  hasLegalPaper, projectId, imageUrl, description, deepAnalysis).
- HttpAVMService.estimateViaAi now branches on `useV2`: v2 calls the new
  aiClient.predictV2() → POST /avm/v2/predict on the Python service,
  mapping floodZoneRisk enum → 0..1 float and computing
  building_age_years from yearBuilt. v1 path gets all the inline
  descriptors wired through so non-propertyId calls no longer lose
  context.
- AiServiceClient gets AiPredictV2Request / AiPredictV2Response types
  mirroring libs/ai-services/app/models/avm_v2.py::AVMv2PredictRequest
  (which already accepts all 7 numeric/boolean v2 fields — no Python
  change needed).
- Register PredictValuationHandler in AnalyticsModule.
- New route POST /analytics/valuation on AnalyticsController:
  JwtAuthGuard + QuotaGuard + EndpointRateLimitGuard (10/min),
  @RequireQuota('analytics_queries'), full Swagger doc. Total endpoint
  count 179 → 180.

Frontend
- Extend ValuationRequest with useV2, 3 distance-km fields,
  floodZoneRisk, hasElevator/Parking/Pool + export FloodZoneRisk type
  and FLOOD_RISK_OPTIONS.
- valuationApi.predict() body mapping now includes v2 fields and renames
  'areaM2' → 'area' to match the backend DTO contract.
- valuationFormSchema gains matching optional Zod fields + exports
  FLOOD_RISK_OPTIONS for the form.
- valuation-form.tsx gets:
  * Image upload hardening: MIME+size validation (JPG/PNG ≤5MB) before
    preview, role="progressbar" + aria-labels on the progress bar,
    role="alert" + data-testid="image-upload-error" on errors. Matches
    the upload-progress part of the task/tec-2725 commit 4ee0129 that
    was previously parked as blocked.
  * New Sparkles-branded "Mô hình v2 (Ensemble)" toggle alongside the
    existing Bot-branded "Phân tích chuyên sâu" toggle.
  * Collapsible "Đặc trưng mở rộng (AVM v2)" section with distance
    inputs, flood-risk select, and three amenity checkboxes.
  * handleFormSubmit passes all v2 fields through to onSubmit.

Python service unchanged — AVMv2PredictRequest already has every field
we send (distance_to_hospital_km, flood_zone_risk as float,
has_elevator/parking/pool, etc.).

Typecheck clean for the valuation surface. Pre-existing errors in
metadata.spec.ts and transfer-wizard-client.tsx are unrelated and left
for a follow-up.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-19 06:49:57 +07:00

274 lines
7.1 KiB
TypeScript

import { Injectable } from '@nestjs/common';
import { LoggerService } from '@modules/shared';
export interface AiPredictRequest {
area: number;
district: string;
city: string;
property_type: string;
bedrooms?: number;
bathrooms?: number;
floors?: number;
frontage?: number;
road_width?: number;
year_built?: number | null;
has_legal_paper?: boolean;
}
export interface AiPredictResponse {
estimated_price_vnd: number;
confidence: number;
price_per_m2: number;
price_range_low: number;
price_range_high: number;
}
/**
* AVM v2 request — extended feature set for residential ensemble.
* Matches `AVMv2PredictRequest` in libs/ai-services/app/models/avm_v2.py.
*/
export interface AiPredictV2Request {
district: string;
city: string;
property_type: string;
area_m2: number;
distance_to_cbd_km?: number;
distance_to_metro_km?: number;
distance_to_school_km?: number;
distance_to_hospital_km?: number;
distance_to_park_km?: number;
distance_to_mall_km?: number;
flood_zone_risk?: number;
neighborhood_score?: number;
rooms?: number;
floor_level?: number;
total_floors?: number;
direction?: string;
floor_ratio?: number;
building_age_years?: number;
has_elevator?: boolean;
has_parking?: boolean;
has_pool?: boolean;
has_legal_paper?: boolean;
developer_reputation?: number;
avg_price_district_3m_vnd_m2?: number;
listing_density?: number;
absorption_rate?: number;
dom_avg?: number;
price_momentum_30d?: number;
yoy_change?: number;
renovation_score?: number;
view_quality?: number;
interior_quality?: number;
noise_level?: number;
natural_light?: number;
month?: number;
quarter?: number;
is_year_end?: boolean;
}
export interface AiPredictV2FeatureImportance {
feature: string;
importance: number;
}
export interface AiPredictV2Comparable {
district: string;
property_type: string;
area_m2: number;
price_vnd: number;
price_per_m2_vnd: number;
similarity_score: number;
}
export interface AiPredictV2Response {
estimated_price_vnd: number;
confidence: number;
price_per_m2_vnd: number;
price_range_low_vnd: number;
price_range_high_vnd: number;
drivers?: AiPredictV2FeatureImportance[];
comparables?: AiPredictV2Comparable[];
model_version?: string;
ensemble_method?: string;
}
export interface AiIndustrialPredictRequest {
province: string;
region: string;
park_occupancy_rate: number;
park_area_ha: number;
park_age_years: number;
distance_to_port_km: number;
distance_to_airport_km: number;
distance_to_highway_km: number;
property_type: string;
area_m2: number;
ceiling_height_m?: number;
floor_load_ton_m2?: number;
power_capacity_kva?: number;
building_coverage?: number;
loading_docks?: number;
zoning?: string;
industry_demand_index?: number;
fdi_province_musd?: number;
labor_cost_province_vnd?: number;
logistics_connectivity_score?: number;
}
export interface AiIndustrialComparable {
park_name: string;
province: string;
property_type: string;
area_m2: number;
rent_usd_m2: number;
similarity_score: number;
}
export interface AiIndustrialFeatureImportance {
feature: string;
importance: number;
}
export interface AiIndustrialPredictResponse {
estimated_rent_usd_m2: number;
confidence: number;
rent_range_low_usd_m2: number;
rent_range_high_usd_m2: number;
annual_rent_usd_m2: number;
total_monthly_rent_usd: number;
comparables: AiIndustrialComparable[];
drivers: AiIndustrialFeatureImportance[];
model_version: string;
}
export interface AiModerationRequest {
text: string;
context?: string;
}
export interface AiModerationFlag {
category: string;
severity: string;
matched_text: string;
reason: string;
}
export interface AiModerationResponse {
is_flagged: boolean;
score: number;
flags: AiModerationFlag[];
cleaned_text: string | null;
}
export interface AiNeighborhoodPOICounts {
education: number;
healthcare: number;
transport: number;
shopping: number;
greenery: number;
safety: number;
}
export interface AiNeighborhoodScoreRequest {
district: string;
city: string;
poi_counts: AiNeighborhoodPOICounts;
}
export interface AiNeighborhoodScoreResponse {
district: string;
city: string;
education_score: number;
healthcare_score: number;
transport_score: number;
shopping_score: number;
greenery_score: number;
safety_score: number;
total_score: number;
poi_counts: Record<string, number>;
algorithm_version: string;
}
export const AI_SERVICE_CLIENT = Symbol('AI_SERVICE_CLIENT');
export interface IAiServiceClient {
predict(req: AiPredictRequest): Promise<AiPredictResponse>;
predictV2(req: AiPredictV2Request): Promise<AiPredictV2Response>;
predictIndustrial(req: AiIndustrialPredictRequest): Promise<AiIndustrialPredictResponse>;
moderate(req: AiModerationRequest): Promise<AiModerationResponse>;
scoreNeighborhood(req: AiNeighborhoodScoreRequest): Promise<AiNeighborhoodScoreResponse>;
isAvailable(): Promise<boolean>;
}
@Injectable()
export class AiServiceClient implements IAiServiceClient {
private readonly baseUrl: string;
private readonly apiKey: string;
private readonly timeoutMs: number;
constructor(private readonly logger: LoggerService) {
this.baseUrl = process.env['AI_SERVICE_URL'] ?? 'http://localhost:8000';
this.apiKey = process.env['AI_SERVICE_API_KEY'] ?? '';
this.timeoutMs = Number(process.env['AI_SERVICE_TIMEOUT_MS']) || 5000;
}
async predict(req: AiPredictRequest): Promise<AiPredictResponse> {
return this.post<AiPredictResponse>('/avm/predict', req);
}
async predictV2(req: AiPredictV2Request): Promise<AiPredictV2Response> {
return this.post<AiPredictV2Response>('/avm/v2/predict', req);
}
async predictIndustrial(req: AiIndustrialPredictRequest): Promise<AiIndustrialPredictResponse> {
return this.post<AiIndustrialPredictResponse>('/avm/industrial/predict', req);
}
async moderate(req: AiModerationRequest): Promise<AiModerationResponse> {
return this.post<AiModerationResponse>('/moderation/check', req);
}
async scoreNeighborhood(
req: AiNeighborhoodScoreRequest,
): Promise<AiNeighborhoodScoreResponse> {
return this.post<AiNeighborhoodScoreResponse>('/neighborhood/score', req);
}
async isAvailable(): Promise<boolean> {
try {
const response = await fetch(`${this.baseUrl}/health`, {
method: 'GET',
signal: AbortSignal.timeout(2000),
});
return response.ok;
} catch {
return false;
}
}
private async post<T>(path: string, body: unknown): Promise<T> {
const url = `${this.baseUrl}${path}`;
const headers: Record<string, string> = {
'Content-Type': 'application/json',
};
if (this.apiKey) {
headers['X-API-Key'] = this.apiKey;
}
const response = await fetch(url, {
method: 'POST',
headers,
body: JSON.stringify(body),
signal: AbortSignal.timeout(this.timeoutMs),
});
if (!response.ok) {
const text = await response.text().catch(() => '');
throw new Error(`AI service ${path} returned ${response.status}: ${text}`);
}
return response.json() as Promise<T>;
}
}